Abstract
A critical transportation infrastructure integrated with the Internet of Things based wireless sensor network, operates as a cyber-physical system. However, the new form of IoT enabled transportation infrastructure is susceptible to cyber-physical attacks in the sensing area, due to inherent cyber vulnerabilities of IoT devices and deficient control barriers that could protect it. Traditional risk assessment processes, consider the physical and cyber space as isolated environments, resulting in IoT enabled transportation infrastructure not being assessed by stakeholders (i.e., operators, civil and security engineers) for cyber-physical attacks. In this paper, a new risk assessment approach for cyber-physical attacks against IoT based wireless sensor network is proposed. The approach relies on the identification and proposal of novel cyber-physical characteristics, in the aspect of threat source (e.g., motives), vulnerability (e.g., lack of authentication mechanisms) and types of physical impacts (e.g., casualties). Cyber-physical risk is computed as a product of the level and importance of these characteristics. Monte Carlo simulations and sensitivity analysis are performed to evaluate the results of an IoT enabled bridge subjected to cyber-physical attack scenarios. The results indicate that 76.6% of simulated cases have high-risk and control barriers operating in physical and cyber space can reduce the cyber-physical risk by 71.8%. Additionally, cyber-physical risk differentiates when the importance of the characteristics that are considered during risk assessment is overlooked. The approach is of interest to stakeholders who attempt to incorporate the cyber domain in risk assessment procedures of their system.
Funder
University College Dublin
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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